Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017JD026613 |
Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes | |
Iizumi, Toshichika1; Takikawa, Hiroki2; Hirabayashi, Yukiko3; Hanasaki, Naota4; Nishimori, Motoki1 | |
2017-08-16 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2017 |
卷号 | 122期号:15 |
文章类型 | Article |
语种 | 英语 |
国家 | Japan |
英文摘要 | The use of different bias-correction methods and global retrospective meteorological forcing data sets as the reference climatology in the bias correction of general circulation model (GCM) daily data is a known source of uncertainty in projected climate extremes and their impacts. Despite their importance, limited attention has been given to these uncertainty sources. We compare 27 projected temperature and precipitation indices over 22 regions of the world (including the global land area) in the near (2021-2060) and distant future (2061-2100), calculated using four Representative Concentration Pathways (RCPs), five GCMs, two bias-correction methods, and three reference forcing data sets. To widen the variety of forcing data sets, we developed a new forcing data set, S14FD, and incorporated it into this study. The results show that S14FD is more accurate than other forcing data sets in representing the observed temperature and precipitation extremes in recent decades (1961-2000 and 1979-2008). The use of different bias-correction methods and forcing data sets contributes more to the total uncertainty in the projected precipitation index values in both the near and distant future than the use of different GCMs and RCPs. However, GCM appears to be the most dominant uncertainty source for projected temperature index values in the near future, and RCP is the most dominant source in the distant future. Our findings encourage climate risk assessments, especially those related to precipitation extremes, to employ multiple bias-correction methods and forcing data sets in addition to using different GCMs and RCPs. |
英文关键词 | climate extremes bias correction meteorological forcing data set uncertainty |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000408349500007 |
WOS关键词 | CLIMATE EXTREMES ; INDEXES ; MODEL ; CMIP5 ; 20TH-CENTURY ; HUMIDITY |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/33731 |
专题 | 气候变化 |
作者单位 | 1.Natl Agr & Food Res Org, Inst Agroenvironm Sci, Tsukuba, Ibaraki, Japan; 2.KOZO KEIKAKU Engn Inc, Tokyo, Japan; 3.Univ Tokyo, Inst Ind Sci, Tokyo, Japan; 4.Natl Inst Environm Studies, Tsukuba, Ibaraki, Japan |
推荐引用方式 GB/T 7714 | Iizumi, Toshichika,Takikawa, Hiroki,Hirabayashi, Yukiko,et al. Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2017,122(15). |
APA | Iizumi, Toshichika,Takikawa, Hiroki,Hirabayashi, Yukiko,Hanasaki, Naota,&Nishimori, Motoki.(2017).Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,122(15). |
MLA | Iizumi, Toshichika,et al."Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 122.15(2017). |
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